Prediction model of in-hospital mortality risk in intensive care unit patients with cardiac arrest: a multicenter retrospective cohort study based on an ensemble model.

Journal: Frontiers in cardiovascular medicine
Published Date: May 20, 2025

Abstract

BACKGROUND: In-hospital cardiac arrest (IHCA) is a major adverse event with a high death risk. Machine learning (ML) models of prognosis in cardiac arrest (CA) patients have been established, but there are some interferences in their clinical application. This study developed an ensemble learning (EL) model based on clinical information to predict IHCA patient death risk.

Authors

  • Li Liu
    Metanotitia Inc., Shenzhen, China.
  • Wei-Wei Lai
    Department of Emergency Medicine, Tianjin Medical University General Hospital, Tianjin, China.
  • Bo-Wen Li
    School of Civil and Environmental Engineering, Harbin Institute of Technology, Shenzhen, 518055, China.
  • Shu-Hang Wang
    Department of Emergency Medicine, Tianjin Medical University General Hospital, Tianjin, China.
  • Mu-Ming Yu
    Department of Emergency Medicine, Tianjin Medical University General Hospital, Tianjin, China.
  • Yan-Cun Liu
    Department of Emergency Medicine, Tianjin Medical University General Hospital, Tianjin, China.
  • Yan-Fen Chai
    Department of Emergency Medicine, Tianjin Medical University General Hospital, Tianjin, China.

Keywords

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